As another approach to performing temporal self-supervised learning, a pretext task was designed to validate whether or not the frames of a video are in the right order successive to performing temporal shuffling [1]}. Using this approach, the performance of video classification on large datasets, for instance for action recognition, was improved. Later, the Odd-One-Out Network [2]} was proposed with a similar objective. In this case, given a few videos, the objective was to identity which video does not have the correct temporal order.
